Results 51 to 60 of about 12,223 (205)
Pre-Processing and Modeling Tools for Bigdata
Foundations of Computing and Decision Sciences, 2016 Modeling tools and operators help the user / developer to identify the processing field on the top of the sequence and to send into the computing module only the data related to the requested result.
Hashem Hadi, Ranc Daniel
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MR-IDPSO: A Novel Algorithm for Large-Scale Dynamic Service Composition
Tsinghua Science and Technology, 2015 In the era of big data, data intensive applications have posed new challenges to the field of service composition. How to select the optimal composited service from thousands of functionally equivalent services but different Quality of Service (QoS ...
Yanping Zhang, Zihui Jing, Yiwen Zhang
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Three Algorithms for Parallel Graph Summarization
Expert Systems, Volume 43, Issue 1, January 2026.ABSTRACT Most graph summarization algorithms are tailored to a specific graph summary model and were designed for one‐time computations only, that is, batch‐based computations. We developed a universal approach for parallel graph summarization and three algorithms to compute graph summaries—a batch‐based algorithm for static graphs, an incremental ...
Till Blume +3 more
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Network Motif Detection: Algorithms, Parallel and Cloud Computing, and Related Tools
Tsinghua Science and Technology, 2013 Network motif is defined as a frequent and unique subgraph pattern in a network, and the search involves counting all the possible instances or listing all patterns, testing isomorphism known as NP-hard and large amounts of repeated processes for ...
Wooyoung Kim, Martin Diko, Keith Rawson
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The Performance Optimization of Big Data Processing by Adaptive MapReduce Workflow
IEEE Access, 2022 The discussion context of this paper is big data processing of MapReduce by volunteer computing in dynamic and opportunistic environments. This paper conducts a series of simulations to explore the relationship between the overall performance of ...
Wei Li, Maolin Tang
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Design of a TSK Rule‐Based Model With Granular Rules and Ensemble Learning in Big Data
Complexity, Volume 2026, Issue 1, 2026.Nowadays, the management and analysis of big data have become major challenges for researchers in the field of data mining. The increasing rate of data generation, along with the need to extract meaningful patterns, highlights the necessity of developing scalable big data analysis methods.
Mohammad Nematpour +4 more
wiley +1 more source
Practical scalable image analysis and indexing using Hadoop [PDF]
, 2012 The ability to handle very large amounts of image data is important for image analysis, indexing and retrieval applications. Sadly, in the literature, scalability aspects are often ignored or glanced over, especially with respect to the intricacies of ...
Hare, Jonathon S. +5 more
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Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks
International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa +5 more
wiley +1 more source
Experimenting sensitivity-based anonymization framework in apache spark
Journal of Big Data, 2018 One of the biggest concerns of big data and analytics is privacy. We believe the forthcoming frameworks and theories will establish several solutions for the privacy protection.
Mohammed Al-Zobbi +2 more
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CloudDOE: a user-friendly tool for deploying Hadoop clouds and analyzing high-throughput sequencing data with MapReduce. [PDF]
PLoS ONE, 2014 BackgroundExplosive growth of next-generation sequencing data has resulted in ultra-large-scale data sets and ensuing computational problems. Cloud computing provides an on-demand and scalable environment for large-scale data analysis.
Wei-Chun Chung +9 more
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